The present invention relates to a tire design method.
Since a tread pattern of a pneumatic tire has significant influence on hydroplaning performance, braking performance, and noises, there are demands for designs of tire tread patterns having optimized topology and shapes.
When a tire tread pattern is designed, a design plan satisfying performance requirements is made based on knowledge of the related art, experiences, and limitations on designing. One approach for verification of the design is to check whether the performance requirements are satisfied or not using a structural analysis. When it is revealed at this stage that the performance requirements are not satisfied, the design is corrected, and a structural analysis is conducted again to verify the design. This process is repeated until the performance requirements are satisfied, and a design plan is thereby finalized.
According to the design method in the related art, no guarantee is given on whether a design plan finalized within a range set based on design limitations provides optimal values or not. Since the method involves the process of repeating designing, structural analysis, and re-designing, a design task will require an enormous amount of time. Under the circumstance, various methods for optimizing a tire through numerical optimizations have been proposed in an intention to allow efficient designing (see U.S. Pat. Nos. 5,710,718A, 6,230,112B1, 6,531,012B2, Japanese Patent Laid-Open No. JP-A-2005-008011).
In general, a generic algorithm is frequently used for numerical optimizations to optimize the shape of a tire tread pattern (for example, see U.S. Pat. No. 5,710,718A). However, there is a great number of individual genes in the case of pattern designing of a wide area. Then, the computational cost is increased, and the approach is not effective enough to be used for practical design tasks.
According to a method of optimizing a tread pattern shape in the related art, elements which directly determine a tread pattern shape such as the length and shape of each edge of a block are used as design variables. For this reason, the method is limited to tread pattern shapes which can be defined by parameters having a fixed form such as straight lines and sine curves. Therefore, the method is limited in the range for searching an optimal solution, and it has a problem in that a mesh forming finite elements must be re-created each time a design variable is changed.
Layout optimization techniques employing the finite element method includes the ECAT (Evolutional Clustering Algorithm for Topological Optimization). According to the ECAT, a structure of interest is regarded as an individual body, and elements are classified according to the magnitudes of their evaluation indices which are determined according to the problem to be solved. A global distribution of the evaluation indices in the structure is obtained, and actions of removing or adding each class of elements having small evaluation indices one after another are regarded as behaviors. Then, a layout is decided through evolution of such behaviors. Although the ECAT has been used for layout optimization problems in mechanical structures such as cantilevers, no application of this method to a tire tread pattern has been known.
Methods of optimizing structures using a basis vector process are disclosed in JP-A-2002-149717 and JP-A-2005-065996. JP-A-2002-149717 and JP-A-2002-065996 disclose optimization of the shape of a disk arm and optimization of the shape of a golf club head, respectively. Both of the publications address methods for optimizing relatively simple shapes and do not propose optimization of complicated shapes such as tire tread patterns.